Federal and State Tax law has become so complex that it is now estimated that each year Americans alone use over 6 billion person hours, and spend nearly 4 billion dollars, in an effort to comply with Federal and State Tax statutes. Given this level of complexity and cost, it is not surprising that more and more taxpayers find it necessary to obtain help, in one form or another, to prepare their taxes. Tax return preparation systems, such as tax return preparation software programs and applications, represent a potentially flexible, highly accessible, and affordable source of tax preparation assistance. However, traditional tax return preparation systems do not provide adequate real-time assistance to users.
For instance, users of traditional tax return preparation systems enter most of their data by hand. Entering data by hand often leads to inadvertent typing errors or other kinds of errors. Many traditional tax return preparation systems often do not provide any assistance at all when it comes to detecting errors in data entries made by users. Other traditional tax return preparation systems allow a user to upload an image of financial documents and perform optical character recognition (OCR) analysis on the image in order to automatically import data from the financial document. However, such OCR analysis is often littered with errors. In some cases, the OCR analysis fails to correctly recognize data entries. In other cases, the OCR analysis may leave many fields blank.
One reason that traditional financial systems do not provide adequate OCR recognition is due to the extremely large processing and storage resources needed to analyze large volumes of documents having large numbers of data entries.
When errors in OCR data are not caught quickly, or at all, there can be significant consequences to users. For example, a user may pay too much tax or a user may pay not enough tax and have late fees and/or other IRS penalties imposed. When errors are discovered, a user may have to redo and refile taxes for previous years as well.
Moreover, the types of drawbacks associated with traditional tax return preparation systems are found in other financial systems as well. For example, many people use electronic financial systems to manage personal investments, banking, loans, retirement plans, and even to make and stay within a budget. OCR errors in these systems can have very costly real world consequences to users. Yet, these typically rigid systems do not adequately provide improved OCR analysis.
What is needed is a method and system for providing augmented OCR analysis of financial documents that is quick and accurate without using unduly large processing and storage resources.